Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: http://hdl.handle.net/10419/229513
Autoren: 
Pesaran, M. Hashem
Yang, Cynthia Fan
Datum: 
2020
Schriftenreihe/Nr.: 
CESifo Working Paper No. 8695
Zusammenfassung: 
This paper develops an individual-based stochastic network SIR model for the empirical analysis of the Covid-19 pandemic. It derives moment conditions for the number of infected and active cases for single as well as multigroup epidemic models. These moment conditions are used to investigate identification and estimation of recovery and transmission rates. The paper then proposes simple moment-based rolling estimates and shows them to be fairly robust to the well-known under-reporting of infected cases. Empirical evidence on six European countries match the simulated outcomes, once the under-reporting of infected cases is addressed. It is estimated that the number of reported cases could be between 3 to 9 times lower than the actual numbers. Counterfactual analysis using calibrated models for Germany and UK show that early intervention in managing the infection is critical in bringing down the reproduction numbers below unity in a timely manner.
Schlagwörter: 
Covid-19
multigroup SIR model
basic and effective reproduction numbers
rolling window estimates of the transmission rate
method of moments
calibration and counterfactual analysis.
JEL: 
C13
C15
C31
D85
I18
J18
Dokumentart: 
Working Paper

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